Navigating AI Integration in Career and Technical Education: Diffusion Challenges, Opportunities, and Decisions DOI Creative Commons
Jeffrey C. Sun, Taylor L. Pratt

Education Sciences, Год журнала: 2024, Номер 14(12), С. 1285 - 1285

Опубликована: Ноя. 25, 2024

This review paper explores the integration of artificial intelligence (AI) in career and technical education (CTE). CTE is an educational domain often overlooked discussions about teaching learning notably omitted extant literature AI’s application settings. Although much existing focuses on AI K-12 higher education, faces distinct challenges opportunities both because programming more hands-on industry-connected. paper, grounded Diffusion Innovations theory, examines tool adoption processes among educators by analyzing barriers opportunities. Key findings suggest that while offers significant benefits, its hindered systemic factors. contributes to highlighting importance contextualizing within pedagogical practices industry partnerships CTE. It emphasizes need for targeted strategies address CTE-specific challenges, including robust infrastructure, equitable resource distribution, fostering a culture innovation educators. The implications this work underscore potential bridge gap between workforce demands, positioning programs as critical sites preparing students next phase under Industry 5.0.

Язык: Английский

Benefits and Challenges of Collaboration between Students and Conversational Generative Artificial Intelligence in Programming Learning: An Empirical Case Study DOI Creative Commons
Wanxin Yan,

Taira Nakajima,

Ryo Sawada

и другие.

Education Sciences, Год журнала: 2024, Номер 14(4), С. 433 - 433

Опубликована: Апрель 20, 2024

The utilization of conversational generative artificial intelligence (Gen AI) in learning is often seen as a double-edged sword that may lead to superficial learning. We designed and implemented programming course focusing on collaboration between students Gen AI. This study explores the dynamics such collaboration, students’ communication strategies with AI, perceived benefits, challenges encountered. Data were collected from class observations, surveys, final reports, dialogues semi-structured in-depth interviews. results showed effective AI could enhance meta-cognitive self-regulated skills positively impact human-to-human communication. further revealed difficulties individual differences collaborating complex tasks. Overall, partner, rather than just tool, enables sustainable independent learning, beyond specific tasks at given time.

Язык: Английский

Процитировано

11
Andragogy in the Age of AI DOI
Valerie A. Storey,

Amiee Wagner

Advances in educational technologies and instructional design book series, Год журнала: 2025, Номер unknown, С. 25 - 44

Опубликована: Янв. 17, 2025

This chapter explores the transformative impact of Artificial Intelligence (AI) on adult education, drawing foundational work Malcolm Knowles, who emphasized necessity for adaptive and self-directed learning practices. It examines rapid technological advancements since Knowles' time, highlighting how modern AI technologies, particularly Generative AI, are reshaping landscape education. By aligning with andragogical principles, educators can enhance experience while addressing potential challenges such as algorithmic bias inequity. The is structured into three sections: first AI-based science its congruence principles; second assesses evolving nature andragogy in digital era; third projects future pathways integrating learning, emphasizing implications education delivery knowledge production

Язык: Английский

Процитировано

1
The role of generative AI in education: Perceptions of Saudi students DOI
Aminah Saad Aldossary, Alia Abdullah Aljindi, Jamilah Mohammed Alamri

и другие.

Contemporary Educational Technology, Год журнала: 2024, Номер 16(4), С. ep536 - ep536

Опубликована: Окт. 22, 2024

<b>Purpose:</b> This study aims to provide an analysis of students’ perceptions the role generative artificial intelligence (GenAI) tools in education, through five axes: (1) level knowledge and awareness, (2) acceptance readiness, (3) GenAI (4 (level awareness potential concerns challenges, (5) The impact on achieving sustainable development goals education.<br /> <b>Materials methods:</b> followed a descriptive quantitative methodology based surveying questionnaire. sample consisted 1390 students from 15 Saudi universities.<br <b>Results:</b> have positive towards as high adopting these tools. In addition, are highly aware improving their understanding complex concepts, developing skills, self-efficacy, learning outcomes, providing feedback, making meaningful. results also confirm general challenges. A relationship exists between scientific specializations, computer sciences showed greater regarding whereas agricultural goals.<br <b>Conclusions:</b> offers valuable insights adoption higher there is urgent need consider appropriate use policies, spreading creating systems capable detecting unethical cases.

Язык: Английский

Процитировано

4
Generative AI for Consumer Behavior Prediction: Techniques and Applications DOI Open Access
Mitra Madanchian

Sustainability, Год журнала: 2024, Номер 16(22), С. 9963 - 9963

Опубликована: Ноя. 15, 2024

Generative AI techniques, such as Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformers, have revolutionized consumer behavior prediction by enabling the synthesis of realistic data extracting meaningful insights from large, unstructured datasets. However, despite their potential, effectiveness these models in practical applications remains inadequately addressed existing literature. This study aims to investigate how generative can effectively enhance implications for real-world marketing customer engagement. By systematically reviewing 31 studies focused on e-commerce, energy modeling, public health, we identify contributions improving personalized marketing, inventory management, retention. Specifically, transformer excel at processing complicated sequential real-time insights, while GANs VAEs are effective generating predicting behaviors churn purchasing intent. Additionally, this review highlights significant challenges, including privacy concerns, integration computing resources, limited applicability scenarios.

Язык: Английский

Процитировано

4
AI and the Future of Strategic Communication DOI
Karen E. Sutherland

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Exploring the capabilities of GenAI for oral cancer consultations in remote consultations DOI Creative Commons
Yutao Xiong,

Hao-Nan Liu,

Y. Zeng

и другие.

BMC Oral Health, Год журнала: 2025, Номер 25(1)

Опубликована: Фев. 20, 2025

Generative artificial intelligence (GenAI) has demonstrated potential in remote consultations, yet its capacity to comprehend oral cancer not been fully evaluated. The objective of this study was evaluate the accuracy, reliability and validity GenAI addressing questions related consultations for cancer. A search conducted on telemedicine platforms China, summarizing patients' inquiries regarding panel board-certified surgeons compiled reference answers these questions. GPT-3.5-turbo GPT-4o were tasked answer specific cancer, with their responses recorded. assessed using qualitative quantitative measures, including number key points, text length, lexical density, a Likert scale. chi-square test utilized detect differences data, while Kruskal-Wallis test, Mann-Whitney U t-test data. total 34 included, covering basic, etiology, diagnosis, intervention, prognosis. GPT-3.5-Turbo an overall accuracy rate 77.50% analysis, 88.20%. average scores GPT-3.5Turbo 3.96 4.35, respectively, statistically significant differences. close terms but significantly lower length density. marginal advantage, although no response observed between GPT-4o. Moreover, outperformed validity, making it more appropriate consultation scenarios.

Язык: Английский

Процитировано

0
Generative AI in Pandemic Prediction DOI
Parisa Tavana,

Mojgan Zareinejad

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0
Revolutionizing Market Research with Artificial Intelligence DOI

J. K. Teutloff

IGI Global eBooks, Год журнала: 2025, Номер unknown, С. 413 - 434

Опубликована: Фев. 25, 2025

Startups often operate in environments filled with uncertainty, where the lack of reliable market data and high costs traditional research methods can severely limit their ability to validate customer demand. These challenges contribute failure rate early-stage ventures, as many struggle achieve product-market fit before exhausting financial resources. However, advancements Artificial Intelligence (AI), particularly AI-generated synthetic large language models (LLMs), offer a transformative opportunity for startups. technologies revolutionize by enabling accurate scalable demand validation, even limited data. This paper explores how LLMs help startups overcome limitations enhance research, ultimately improving chances success.

Язык: Английский

Процитировано

0
Understanding how to assess the impact of Artificial Intelligence on learning: a systematic review DOI
Marine Cloux, Davy Monticolo, Raphaël Bary

и другие.

Interactive Learning Environments, Год журнала: 2025, Номер unknown, С. 1 - 15

Опубликована: Март 3, 2025

Язык: Английский

Процитировано

0
Yapay Zekâ ve Liderlik: Dönüştürücü Liderlik Tarzının Çalışan Tutumlarına Etkisi DOI Creative Commons
Rüveyde Pabuçcu, Ömer Faruk İşçan

Uluslararası Ekonomi İşletme ve Politika Dergisi, Год журнала: 2025, Номер 9(1), С. 195 - 210

Опубликована: Март 24, 2025

Bu araştırmanın amacı banka çalışanlarının yapay zekâ genel tutumları ile dönüştürücü liderlik tarzı arasındaki ilişkiyi incelemektir. Çalışmada Erzurum ilinde kamu ve özel bankalarda çalışan zekâyı aktif kullanan 295 kişinin katıldığı anket verileri analiz edilmiştir. Veriler, tanımlayıcı istatistikler, t-testleri, ANOVA, korelasyon, regresyon, açımlayıcı faktör analizi doğrulayıcı analizleri değerlendirilmiştir. Elde edilen bulgular, zekâya yönelik pozitif tutum arasında anlamlı bir ilişki bulunduğunu ortaya koymuştur. Bunun yanı sıra, tarzının negatif üzerinde etkisi olmadığı belirlenmiştir. çalışma, bankacılık sektöründeki liderlerin, tarzını benimseyerek, teknolojik değişimlere uyum sağlama konusunda nasıl daha etkili olabileceklerini göstermeyi amaçlamaktadır. açıdan, çalışmanın sektöre özgü bakış açısı politika yapıcılarına tavsiye niteliğinde önemli öneriler sunduğu mevcut literatüre katkı sağladığı söylenebilir.

Процитировано

0